import pandas as pd
from pandas_profiling import ProfileReportGE Aviation - Remaining Useful Life Analysis
Part 2 - Data Overview
Read the Data
df = pd.read_csv("D:\School\FL 2022\ISA 401\GE\ge_data.csv")
df.info()<class 'pandas.core.frame.DataFrame'>
RangeIndex: 100 entries, 0 to 99
Data columns (total 36 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 dataset 100 non-null object
1 esn 100 non-null int64
2 unit 100 non-null int64
3 operator 100 non-null object
4 last_flight_cycle 100 non-null int64
5 last_datetime 100 non-null object
6 mean_tra 100 non-null int64
7 mean_t2 100 non-null float64
8 mean_t24 100 non-null float64
9 mean_t30 100 non-null float64
10 mean_t50 100 non-null float64
11 mean_p2 100 non-null float64
12 mean_p15 100 non-null float64
13 mean_p30 100 non-null float64
14 mean_nf 100 non-null float64
15 mean_nc 100 non-null float64
16 mean_epr 100 non-null float64
17 mean_ps30 100 non-null float64
18 mean_phi 100 non-null float64
19 mean_nrf 100 non-null float64
20 mean_nrc 100 non-null float64
21 mean_bpr 100 non-null float64
22 mean_farb 100 non-null float64
23 mean_htbleed 100 non-null float64
24 mean_nf_dmd 100 non-null int64
25 mean_pcnfr_dmd 100 non-null int64
26 mean_w31 100 non-null float64
27 mean_w32 100 non-null float64
28 mean_X44321P02_op016 100 non-null float64
29 mean_X44321P02_op420 100 non-null float64
30 mean_X54321P01_op116 100 non-null float64
31 mean_X54321P01_op220 100 non-null float64
32 mean_X65421P11_op232 100 non-null float64
33 mean_X65421P11_op630 100 non-null float64
34 total_distance 100 non-null float64
35 rul 100 non-null int64
dtypes: float64(26), int64(7), object(3)
memory usage: 28.2+ KB
Profile Report
profile = ProfileReport(df)profile.to_notebook_iframe()